Abstract As NLP moves into tasks requiring deeper language understanding, inferencing, and reasoning, knowledge-based resources are being increasingly called upon to support and supplement probabilistic and other data-driven methods. PropBank, VerbNet, FrameNet, the Rich Entities[…]

Read More

Abstract Neural Machine Translation (NMT) has gained popularity in recent several years thanks to its simple, yet effective, architecture. Despite the success of achieving state-of-the-art performance for various language pairs, there are several inherent weaknesses[…]

Read More

Abstract In most accounts of semantics, prepositions fly under the radar. I will argue that they should instead be put front and center given their crucial status as linkers of meaning—whether for spatial and temporal[…]

Read More

Abstract The success of machine learning has recently surged, with similar algorithmic approaches effectively solving a variety of human-defined tasks.  Tasks testing how well machines can perceive images and communicate about them have exposed strong[…]

Read More

Abstract Language has rules and rules have exceptions: think the English regular verbs that all add “-ed” and the some 150 irregular verbs that don’t. Children learning languages, as well as statistical models of natural[…]

Read More

Speaker: Shinji Watanabe Title: Distant-talk speech processing toward natural conversation understanding Abstract: Speech recognition and understanding technologies have been rapidly developed in a last decade, and showing significant improvements due to deep learning. With this[…]

Read More

Abstract The brain empowers humans with remarkable abilities to navigate their acoustic environment in highly degraded conditions. This seemingly trivial task for normal hearing listeners is extremely challenging for individuals with auditory pathway disorders, and[…]

Read More